Path Planning for UAV Communication Networks: Related Technologies, Solutions, and Opportunities

被引:15
作者
Luo, Junhai [1 ]
Wang, Zhiyan [1 ]
Xia, Ming [2 ]
Wu, Linyong [2 ]
Tian, Yuxin [1 ]
Chen, Yu [1 ]
机构
[1] Univ Elect Sci & Technol China, Chengdu, Sichuan, Peoples R China
[2] Sichuan Jiuzhou Elect Grp Co Ltd, Jiuzhou, Peoples R China
关键词
Unmanned aerial vehicle communication network; path planning; multi-UAV-assisted path planning; reinforcement learning; UNMANNED AERIAL VEHICLES; JOINT TRAJECTORY DESIGN; THROUGHPUT MAXIMIZATION; SENSOR NETWORKS; LARGE-SCALE; OPTIMIZATION; ENVIRONMENTS; MINIMIZATION; ALLOCATION; ALGORITHM;
D O I
10.1145/3560261
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Path planning has been a hot and challenging field in unmanned aerial vehicles (UAV). With the increasing demand of society and the continuous progress of technologies, UAV communication networks (UAVCN) are also flourishing. The mobility of UAV nodes allows for flexible network deployment, but some challenges are brought, such as power constraints, throughput, cost, and time efficiency. Therefore, path planning is significant for UAVCN. This article presents a review of UAVCN path planning. We first introduce the network structure and performance evaluation of UAVCN. We then investigate the generic UAV path planning algorithms and the path planning algorithms in UAVCN. In this article, the advantages and disadvantages of each path planning algorithm and the functional problems. The challenges faced in path planning for UAVCN, the solutions, state-of-the-art, and representative results are also presented. In addition, we illustrate future research directions for UAVCN path planning as well, which can provide some help to researchers.
引用
收藏
页数:37
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